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» Learning with Local Drift Detection
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CVPR
2007
IEEE
16 years 8 months ago
Robust Click-Point Linking: Matching Visually Dissimilar Local Regions
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
Kazunori Okada, Xiaolei Huang
ECCV
2006
Springer
16 years 7 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann
CVPR
2010
IEEE
16 years 2 months ago
Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes
A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique ut...
Shandong Wu, Brian E. Moore, and Mubarak Shah
IPSN
2004
Springer
15 years 11 months ago
Distributed online localization in sensor networks using a moving target
We describe a novel method for node localization in a sensor network where there are a fraction of reference nodes with known locations. For application-specific sensor networks, ...
Aram Galstyan, Bhaskar Krishnamachari, Kristina Le...
ICCV
2007
IEEE
16 years 7 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...